rfcp/installer/rfcp-server-gpu.spec

# rfcp-server-gpu.spec — GPU-enabled build (CuPy + CUDA 13.x)
# RFCP Iteration 3.6.0
#
# Mode: ONEDIR (directory output, not single exe)
# This is better for CUDA — DLLs load directly without temp extraction
#
# Requirements:
#   pip install cupy-cuda13x fastrlock pyinstaller
#   CUDA Toolkit 13.x installed (winget install Nvidia.CUDA)
#
# Build:
#   cd backend && pyinstaller ../installer/rfcp-server-gpu.spec --clean --noconfirm
#
# Output:
#   backend/dist/rfcp-server/rfcp-server.exe  (+ DLLs in same folder)

import os
import sys
import glob
from PyInstaller.utils.hooks import collect_all, collect_dynamic_libs

backend_path = os.path.abspath(os.path.join(os.path.dirname(SPEC), '..', 'backend'))
print(f"[GPU SPEC] Backend path: {backend_path}")

# ═══════════════════════════════════════════
# Collect CuPy packages
# ═══════════════════════════════════════════
cupy_datas = []
cupy_binaries = []
cupy_hiddenimports = []
cupyb_datas = []
cupyb_binaries = []
cupyb_hiddenimports = []

try:
    cupy_datas, cupy_binaries, cupy_hiddenimports = collect_all('cupy')
    cupyb_datas, cupyb_binaries, cupyb_hiddenimports = collect_all('cupy_backends')
    print(f"[GPU SPEC] CuPy: {len(cupy_binaries)} binaries, {len(cupy_datas)} data files")
except Exception as e:
    print(f"[GPU SPEC] WARNING: CuPy collection failed: {e}")

# NOTE: nvidia pip packages REMOVED - they have cuda12 DLLs that conflict with cupy-cuda13x
# We use CUDA Toolkit 13.x DLLs only

# ═══════════════════════════════════════════
# Collect CUDA Toolkit DLLs (system install)
# ═══════════════════════════════════════════
# Installed via: winget install Nvidia.CUDA
cuda_toolkit_binaries = []
cuda_path = os.environ.get('CUDA_PATH', '')

if cuda_path:
    # Scan BOTH bin\ and bin\x64\ directories
    cuda_bin_dirs = [
        os.path.join(cuda_path, 'bin'),
        os.path.join(cuda_path, 'bin', 'x64'),
    ]

    # Only essential CUDA runtime DLLs (exclude NPP, nvjpeg, nvblas, nvfatbin)
    cuda_dll_patterns = [
        'cublas64_*.dll',
        'cublasLt64_*.dll',
        'cudart64_*.dll',
        'cufft64_*.dll',
        'cufftw64_*.dll',
        'curand64_*.dll',
        'cusolver64_*.dll',
        'cusolverMg64_*.dll',
        'cusparse64_*.dll',
        'nvrtc64_*.dll',
        'nvrtc-builtins64_*.dll',
        'nvJitLink_*.dll',
        'nvjitlink_*.dll',
    ]

    collected_dlls = set()  # Avoid duplicates
    for cuda_bin in cuda_bin_dirs:
        if os.path.isdir(cuda_bin):
            for pattern in cuda_dll_patterns:
                for dll in glob.glob(os.path.join(cuda_bin, pattern)):
                    dll_name = os.path.basename(dll)
                    if dll_name not in collected_dlls:
                        cuda_toolkit_binaries.append((dll, '.'))
                        collected_dlls.add(dll_name)
            print(f"[GPU SPEC] Scanned: {cuda_bin}")

    print(f"[GPU SPEC] CUDA Toolkit ({cuda_path}): {len(cuda_toolkit_binaries)} DLLs")
    for dll, _ in cuda_toolkit_binaries:
        print(f"[GPU SPEC]   {os.path.basename(dll)}")
else:
    print("[GPU SPEC] ERROR: CUDA_PATH not set!")
    print("[GPU SPEC]   Install: winget install Nvidia.CUDA")

# All GPU binaries (CUDA Toolkit only, no nvidia pip packages)
all_gpu_binaries = cuda_toolkit_binaries

if len(all_gpu_binaries) == 0:
    print("[GPU SPEC] ⚠ NO CUDA DLLs FOUND!")
    print("[GPU SPEC]   Install CUDA Toolkit: winget install Nvidia.CUDA")
else:
    print(f"[GPU SPEC] ✅ Total GPU DLLs: {len(all_gpu_binaries)}")

# ═══════════════════════════════════════════
# Collect fastrlock (CuPy dependency)
# ═══════════════════════════════════════════
fl_datas = []
fl_binaries = []
fl_hiddenimports = []
try:
    fl_datas, fl_binaries, fl_hiddenimports = collect_all('fastrlock')
    print(f"[GPU SPEC] fastrlock: {len(fl_binaries)} binaries")
except Exception:
    print("[GPU SPEC] fastrlock not found (optional)")

# ═══════════════════════════════════════════
# PyInstaller Analysis
# ═══════════════════════════════════════════

a = Analysis(
    [os.path.join(backend_path, 'run_server.py')],
    pathex=[backend_path],
    binaries=(
        cupy_binaries + cupyb_binaries +
        fl_binaries + all_gpu_binaries
    ),
    datas=[
        # Include app/ source code
        (os.path.join(backend_path, 'app'), 'app'),
    ] + cupy_datas + cupyb_datas + fl_datas,
    hiddenimports=[
        # ── Uvicorn internals ──
        'uvicorn.logging',
        'uvicorn.loops',
        'uvicorn.loops.auto',
        'uvicorn.loops.asyncio',
        'uvicorn.protocols',
        'uvicorn.protocols.http',
        'uvicorn.protocols.http.auto',
        'uvicorn.protocols.http.h11_impl',
        'uvicorn.protocols.http.httptools_impl',
        'uvicorn.protocols.websockets',
        'uvicorn.protocols.websockets.auto',
        'uvicorn.protocols.websockets.wsproto_impl',
        'uvicorn.lifespan',
        'uvicorn.lifespan.on',
        'uvicorn.lifespan.off',
        # ── FastAPI / Starlette ──
        'fastapi',
        'fastapi.middleware',
        'fastapi.middleware.cors',
        'fastapi.routing',
        'fastapi.responses',
        'fastapi.exceptions',
        'starlette',
        'starlette.routing',
        'starlette.middleware',
        'starlette.middleware.cors',
        'starlette.responses',
        'starlette.requests',
        'starlette.concurrency',
        'starlette.formparsers',
        'starlette.staticfiles',
        # ── Pydantic ──
        'pydantic',
        'pydantic.fields',
        'pydantic_settings',
        'pydantic_core',
        # ── HTTP / networking ──
        'httpx',
        'httpcore',
        'h11',
        'httptools',
        'anyio',
        'anyio._backends',
        'anyio._backends._asyncio',
        'sniffio',
        # ── MongoDB (motor/pymongo) ──
        'motor',
        'motor.motor_asyncio',
        'pymongo',
        'pymongo.errors',
        'pymongo.collection',
        'pymongo.database',
        'pymongo.mongo_client',
        # ── Async I/O ──
        'aiofiles',
        'aiofiles.os',
        'aiofiles.ospath',
        # ── Scientific ──
        'numpy',
        'numpy.core',
        'scipy',
        'scipy.special',
        'scipy.interpolate',
        'shapely',
        'shapely.geometry',
        'shapely.ops',
        # ── Multipart ──
        'multipart',
        'python_multipart',
        # ── Encoding ──
        'email.mime',
        'email.mime.multipart',
        # ── Multiprocessing ──
        'multiprocessing',
        'multiprocessing.pool',
        'multiprocessing.queues',
        'concurrent.futures',
        # ── CuPy + CUDA ──
        'cupy',
        'cupy.cuda',
        'cupy.cuda.runtime',
        'cupy.cuda.driver',
        'cupy.cuda.memory',
        'cupy.cuda.stream',
        'cupy.cuda.device',
        'cupy._core',
        'cupy._core.core',
        'cupy._core._routines_math',
        'cupy._core._routines_logic',
        'cupy._core._routines_manipulation',
        'cupy._core._routines_sorting',
        'cupy._core._routines_statistics',
        'cupy._core._cub_reduction',
        'cupy.fft',
        'cupy.linalg',
        'cupy.random',
        'cupy_backends',
        'cupy_backends.cuda',
        'cupy_backends.cuda.api',
        'cupy_backends.cuda.libs',
        'fastrlock',
        'fastrlock.rlock',
    ] + cupy_hiddenimports + cupyb_hiddenimports + fl_hiddenimports,
    hookspath=[],
    hooksconfig={},
    runtime_hooks=[os.path.join(os.path.dirname(SPEC), 'rthook_cuda_dlls.py')],
    # ── Exclude bloat ──
    excludes=[
        # GUI
        'tkinter',
        'matplotlib',
        'PIL',
        'IPython',
        # Data science bloat
        'pandas',
        'tensorflow',
        'torch',
        'keras',
        # Testing
        'pytest',
        
        # Jupyter
        'jupyter',
        'notebook',
        'ipykernel',
        # gRPC / telemetry (often pulled in by dependencies)
        'grpc',
        'grpcio',
        'google.protobuf',
        'opentelemetry',
        'opentelemetry.sdk',
        'opentelemetry.instrumentation',
        # Ray (too heavy, we use multiprocessing)
        'ray',
        # Other
        'cv2',
        'sklearn',
        'sympy',
    ],
    noarchive=False,
)

pyz = PYZ(a.pure)

# ═══════════════════════════════════════════
# ONEDIR mode: EXE + COLLECT
# ═══════════════════════════════════════════
# Creates: dist/rfcp-server/rfcp-server.exe + all DLLs in same folder
# Better for CUDA — no temp extraction needed

exe = EXE(
    pyz,
    a.scripts,
    [],  # No binaries/datas in EXE — they go in COLLECT
    exclude_binaries=True,  # ONEDIR mode
    name='rfcp-server',
    debug=False,
    bootloader_ignore_signals=False,
    strip=False,
    upx=False,  # Don't compress — CUDA libs need fast loading
    console=True,
    icon=os.path.join(os.path.dirname(SPEC), 'rfcp.ico') if os.path.exists(os.path.join(os.path.dirname(SPEC), 'rfcp.ico')) else None,
)

coll = COLLECT(
    exe,
    a.binaries,
    a.zipfiles,
    a.datas,
    strip=False,
    upx=False,
    upx_exclude=[],
    name='rfcp-server',
)